Merge pull request #3 from Ibtesam-Mahmood/chat

Added Chat Functionality

CHANGELOG.md

@@ -1,3 +1,12 @@
+## [0.1.3] v0.1.3
+
+* Created `chat` program.
+* Added `gptcli config serpapi` program.
+* Added `gptcli config valueserp` program.
+* Added `-c` flag to `gptcli config <key>` subcommands to clear the current key
+* Factored common chat logic between `understand` and `chat` program
+* Added search functionality to `chat` program through `serpapi` and `valueserp`
+
 ## [0.1.2] v0.1.2
 
 * Created `understand` program.

README.md

@@ -1,4 +1,4 @@
-# gpt-npm-cli v0.1.2
+# gpt-npm-cli v0.1.3
 
 A npm package that uses OpenAI + Langchain to perform convenient commands in the terminal.
 
@@ -29,5 +29,7 @@ The following is a list of commands currently configured within the `gptcli`:
 - `gptcli summary`: Summarizes text and webpage contents, uses map reduce to ensure no limits are encountered for the text 
 - `gptcli translate`: Translates the input text to a desired language.
 - `gptcli understand`: Parses a webpage and allows the user to ask questions about its contents in chat format.
+- `gptcli chat`: Runs a chat interface that can be improved with the following functionalities:
+  - Search Functionality: Provided thorugh `SerpAPI` or `ValueSerp`
 
 For more information run the `gptcli help` command.

package.json

@@ -1,6 +1,6 @@
 {
   "name": "gpt-npm-cli",
-  "version": "0.1.2",
+  "version": "0.1.3",
   "description": "\"# gpt-npm-cli\"",
   "exports": "./index.js",
   "type": "module",

src/index.ts

@@ -6,8 +6,9 @@ import figlet from "figlet";
 import ConfigureProgram from "./programs/configure/configure-program.js";
 import TranslateProgram from "./programs/translate-program.js";
 import UnderstandProgram from "./programs/understand-program.js";
+import ChatProgram from "./programs/chat-program.js";
 
-const version = "0.1.2";
+const version = "0.1.3";
 const description =
   "A super charged CLI for interfacing with GPT-3 and other AI services";
 
@@ -33,6 +34,7 @@ async function main(): Promise<void> {
   new ConfigureProgram().configure(cliApp);
   new TranslateProgram().configure(cliApp);
   new UnderstandProgram().configure(cliApp);
+  new ChatProgram().configure(cliApp);
 
   // Parse the args for the program
   await cliApp.parseAsync(process.argv);

src/langchain/helpers/cli-chat-helper.ts

@@ -0,0 +1,68 @@
+import * as readline from "readline";
+
+interface ChatOptions {
+  runner: (input: string, history: string[]) => Promise<string>;
+  historyUpdate?: (
+    input: string,
+    output: string,
+    history: string[]
+  ) => string[];
+  inputTitle?: string;
+}
+
+function defaultHistoryUpdate(
+  input: string,
+  output: string,
+  history: string[]
+): string[] {
+  return [...history, `User: ${input}`, `Chat: ${output}`];
+}
+
+async function cliChatHelper(options: ChatOptions): Promise<string[]> {
+  const userInputString = `----------\n${
+    options.inputTitle ?? "Input"
+  }:\n----------`;
+  const chatInputString = `----------\nResponse:\n----------`;
+  const rl = readline.createInterface({
+    input: process.stdin,
+    output: process.stdout,
+  });
+
+  // State
+  let chatHistory: string[] = [];
+
+  // start the chat
+  console.log();
+  console.log('Type ".." to exit');
+  console.log();
+  console.log(userInputString);
+  rl.on("line", async (input) => {
+    // Exit the chat
+    if (input === "..") {
+      console.log();
+      console.log("Exiting chat");
+      rl.close();
+      return;
+    }
+
+    // Run the query
+    console.log();
+    const result = await options.runner(input, chatHistory);
+
+    // Print resopnse and next question prompt
+    console.log();
+    console.log(chatInputString);
+    console.log(result);
+    console.log();
+    console.log(userInputString);
+
+    // Update the chat history
+    chatHistory =
+      options.historyUpdate?.(input, result, chatHistory) ??
+      defaultHistoryUpdate(input, result, chatHistory);
+  });
+
+  return chatHistory;
+}
+
+export { cliChatHelper };

src/helpers/langchain/open-ai-chat-helper.ts → src/langchain/open-ai-chat-helper.ts

@@ -1,12 +1,15 @@
+import { initializeAgentExecutor, Tool } from "langchain/agents";
 import { LLMChain, ChatVectorDBQAChain } from "langchain/chains";
-import { LLM, OpenAI } from "langchain/llms";
+import { LLM } from "langchain/llms";
+import { BufferMemory } from "langchain/memory";
 import {
   ChatPromptTemplate,
   HumanMessagePromptTemplate,
   SystemMessagePromptTemplate,
 } from "langchain/prompts";
-import * as readline from "readline";
+import { Calculator, SerpAPI } from "langchain/tools";
 import { VectorStore } from "langchain/vectorstores";
+import { cliChatHelper } from "./helpers/cli-chat-helper.js";
 const { Document: LangDocument } = await import("langchain/document");
 const { loadSummarizationChain } = await import("langchain/chains");
 const { OpenAIChat } = await import("langchain/llms");
@@ -162,8 +165,6 @@ class OpenAiChatHelper {
 
   // Runs a chat on the vector store
   public async understand(info: VectorStore): Promise<void> {
-    const userInputString = `-----\nQuestion:\n-----`;
-    const chatInputString = `-----\nResponse:\n-----`;
     const qaTemplate = `Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.
 
     {context}
@@ -174,48 +175,72 @@ class OpenAiChatHelper {
     Helpful Answer:`;
 
     // define chat vars
-    const chatHistory: string[] = [];
     const chain = ChatVectorDBQAChain.fromLLM(this.model, info, {
       k: 2,
       qaTemplate: qaTemplate,
     });
-    const rl = readline.createInterface({
-      input: process.stdin,
-      output: process.stdout,
-    });
 
-    // start the chat
-    console.log();
-    console.log('Type ".." to exit');
-    console.log();
-    console.log(userInputString);
-    rl.on("line", async (input) => {
-      // Exit the chat
-      if (input === "..") {
-        console.log();
-        console.log("Exiting chat");
-        rl.close();
-        return;
-      }
-
-      // Run the query
-      console.log();
+    // Options for the chat
+    const runner = async (
+      input: string,
+      history: string[]
+    ): Promise<string> => {
       const result = await chain.call({
         question: input,
-        chat_history: chatHistory,
+        chat_history: history,
       });
 
-      // Print resopnse and next question prompt
-      console.log();
-      console.log(chatInputString);
-      console.log(result.text);
-      console.log();
-      console.log(userInputString);
+      return result.text;
+    };
+
+    // Run the chat
+    await cliChatHelper({ runner, inputTitle: "Question" });
+  }
+
+  /*
+ 
+      ____ _           _   
+     / ___| |__   __ _| |_ 
+    | |   | '_ \ / _` | __|
+    | |___| | | | (_| | |_ 
+     \____|_| |_|\__,_|\__|
+                           
+ 
+*/
 
-      // Update the chat history
-      chatHistory.push(`User: ${input}`);
-      chatHistory.push(`Chat: ${result.text}`);
+  public async chat(input?: { tools?: Tool[] }): Promise<void> {
+    // Create chat tools
+    const inputTools: Tool[] = [...(input?.tools ?? []), new Calculator()];
+
+    // Create the chat agent
+    const executor = await initializeAgentExecutor(
+      inputTools,
+      this.model,
+      "chat-conversational-react-description",
+      this.model.verbose
+    );
+
+    // Add memory to the agent
+    executor.memory = new BufferMemory({
+      returnMessages: true,
+      memoryKey: "chat_history",
+      inputKey: "input",
     });
+
+    // Options for the chat helper
+    const runner = async (input: string, _: string[]): Promise<string> => {
+      const result = await executor.call({ input });
+
+      return result.output;
+    };
+    const historyUpdate = (
+      _: string,
+      __: string,
+      history: string[]
+    ): string[] => history;
+
+    // Run the chat
+    await cliChatHelper({ runner, historyUpdate });
   }
 }
 

src/langchain/tools/value-serp-tool.ts

@@ -0,0 +1,102 @@
+import axios from "axios";
+import { Tool } from "langchain/tools";
+
+const value_serp_url = "https://api.valueserp.com/search";
+
+class ValueSerpAPI extends Tool {
+  name: string;
+  description: string;
+  apiKey: string;
+
+  constructor(apiKey: string | undefined) {
+    super();
+
+    if (!apiKey) {
+      throw new Error("No apiKey provided");
+    }
+
+    this.apiKey = apiKey as string;
+    this.name = "search";
+    this.description =
+      "a search engine. useful for when you need to answer questions about current events. input should be a search query.";
+  }
+
+  protected async _call(input: string): Promise<string> {
+    const params = this.getParams(input);
+
+    try {
+      const response = await axios.get(value_serp_url, { params });
+
+      const data = response.data;
+      return this.extractData(data);
+    } catch (e) {
+      throw new Error(`Got error from valueSerpAPI: ${e}`);
+    }
+  }
+
+  private getParams(input: string): any {
+    return {
+      api_key: this.apiKey,
+      q: input,
+      hl: "en",
+      google_domain: "google.com",
+      gl: "us",
+    };
+  }
+
+  private extractData(data: any): string {
+    let response: string = "";
+
+    // answer box
+    if (data?.answer_box?.answers) {
+      const answers = (data.answer_box.answers as any[])
+        .map((e) => `- ${e.answer}`)
+        .join("\n");
+
+      response += "Possible Answers: \n" + answers + "\n\n";
+    }
+
+    // knowledge graph
+    if (data?.knowledge_graph?.description) {
+      response +=
+        "Additional Information: \n- " +
+        data.knowledge_graph.description +
+        "\n\n";
+    }
+
+    // QA results
+    if (data?.related_questions) {
+      const questions = data.related_questions.slice(
+        0,
+        Math.min(3, data.related_questions.length)
+      );
+
+      const results = questions
+        .map((e: any) => `[Q]: ${e.question}\n[A]: ${e.answer}`)
+        .join("\n---\n");
+
+      response += "Related Question Responses: \n" + results + "\n\n";
+    }
+
+    // organic web results, only run if there is no response
+    if (data?.organic_results) {
+      const organgicResults = data.organic_results.slice(
+        0,
+        Math.min(3, data.organic_results.length)
+      );
+      const results = organgicResults
+        .map((e: any) => `- [${e.title}]: ${e.snippet}`)
+        .join("\n");
+      response += "Top Web Results: \n" + results + "\n\n";
+    }
+
+    // defualt response
+    if (response.length === 0) {
+      return "No good search result found";
+    }
+
+    return response;
+  }
+}
+
+export default ValueSerpAPI;